Price Action Analysis Toolkit Development (Part 9): External Flow
Price Action Analysis Toolkit Development (Part 9): External Flow
This article explores a new dimension of analysis using external libraries specifically designed for advanced analytics. These libraries, like pandas, provide powerful tools for processing and interpreting complex data, enabling traders to gain more profound insights into market dynamics. By integrating such technologies, we can bridge the gap between raw data and actionable strategies. Join us as we lay the foundation for this innovative approach and unlock the potential of combining technology with trading expertise.
Price Action Analysis Toolkit Development (Part 8): Metrics Board
Price Action Analysis Toolkit Development (Part 8): Metrics Board
As one of the most powerful Price Action analysis toolkits, the Metrics Board is designed to streamline market analysis by instantly providing essential market metrics with just a click of a button. Each button serves a specific function, whether it’s analyzing high/low trends, volume, or other key indicators. This tool delivers accurate, real-time data when you need it most. Let’s dive deeper into its features in this article.
Adaptive Social Behavior Optimization (ASBO): Two-phase evolution
Adaptive Social Behavior Optimization (ASBO): Two-phase evolution
We continue dwelling on the topic of social behavior of living organisms and its impact on the development of a new mathematical model - ASBO (Adaptive Social Behavior Optimization). We will dive into the two-phase evolution, test the algorithm and draw conclusions. Just as in nature a group of living organisms join their efforts to survive, ASBO uses principles of collective behavior to solve complex optimization problems.
Integration of Broker APIs with Expert Advisors using MQL5 and Python
Integration of Broker APIs with Expert Advisors using MQL5 and Python
In this article, we will discuss the implementation of MQL5 in partnership with Python to perform broker-related operations. Imagine having a continuously running Expert Advisor (EA) hosted on a VPS, executing trades on your behalf. At some point, the ability of the EA to manage funds becomes paramount. This includes operations such as topping up your trading account and initiating withdrawals. In this discussion, we will shed light on the advantages and practical implementation of these features, ensuring seamless integration of fund management into your trading strategy. Stay tuned!
Hidden Markov Models for Trend-Following Volatility Prediction
Hidden Markov Models for Trend-Following Volatility Prediction
Hidden Markov Models (HMMs) are powerful statistical tools that identify underlying market states by analyzing observable price movements. In trading, HMMs enhance volatility prediction and inform trend-following strategies by modeling and anticipating shifts in market regimes. In this article, we will present the complete procedure for developing a trend-following strategy that utilizes HMMs to predict volatility as a filter.
Price Action Analysis Toolkit Development (Part 7): Signal Pulse EA
Price Action Analysis Toolkit Development (Part 7): Signal Pulse EA
Unlock the potential of multi-timeframe analysis with 'Signal Pulse,' an MQL5 Expert Advisor that integrates Bollinger Bands and the Stochastic Oscillator to deliver accurate, high-probability trading signals. Discover how to implement this strategy and effectively visualize buy and sell opportunities using custom arrows. Ideal for traders seeking to enhance their judgment through automated analysis across multiple timeframes.
MQL5 Trading Toolkit (Part 6): Expanding the History Management EX5 Library with the Last Filled Pending Order Functions
MQL5 Trading Toolkit (Part 6): Expanding the History Management EX5 Library with the Last Filled Pending Order Functions
Learn how to create an EX5 module of exportable functions that seamlessly query and save data for the most recently filled pending order. In this comprehensive step-by-step guide, we will enhance the History Management EX5 library by developing dedicated and compartmentalized functions to retrieve essential properties of the last filled pending order. These properties include the order type, setup time, execution time, filling type, and other critical details necessary for effective pending orders trade history management and analysis.
Adaptive Social Behavior Optimization (ASBO): Schwefel, Box-Muller Method
Adaptive Social Behavior Optimization (ASBO): Schwefel, Box-Muller Method
This article provides a fascinating insight into the world of social behavior in living organisms and its influence on the creation of a new mathematical model - ASBO (Adaptive Social Behavior Optimization). We will examine how the principles of leadership, neighborhood, and cooperation observed in living societies inspire the development of innovative optimization algorithms.
News Trading Made Easy (Part 6): Performing Trades (III)
News Trading Made Easy (Part 6): Performing Trades (III)
In this article news filtration for individual news events based on their IDs will be implemented. In addition, previous SQL queries will be improved to provide additional information or reduce the query's runtime. Furthermore, the code built in the previous articles will be made functional.
MQL5 Trading Toolkit (Part 5): Expanding the History Management EX5 Library with Position Functions
MQL5 Trading Toolkit (Part 5): Expanding the History Management EX5 Library with Position Functions
Discover how to create exportable EX5 functions to efficiently query and save historical position data. In this step-by-step guide, we will expand the History Management EX5 library by developing modules that retrieve key properties of the most recently closed position. These include net profit, trade duration, pip-based stop loss, take profit, profit values, and various other important details.
MQL5 Wizard Techniques you should know (Part 51): Reinforcement Learning with SAC
MQL5 Wizard Techniques you should know (Part 51): Reinforcement Learning with SAC
Soft Actor Critic is a Reinforcement Learning algorithm that utilizes 3 neural networks. An actor network and 2 critic networks. These machine learning models are paired in a master slave partnership where the critics are modelled to improve the forecast accuracy of the actor network. While also introducing ONNX in these series, we explore how these ideas could be put to test as a custom signal of a wizard assembled Expert Advisor.
Integrating Discord with MetaTrader 5: Building a Trading Bot with Real-Time Notifications
Integrating Discord with MetaTrader 5: Building a Trading Bot with Real-Time Notifications
In this article, we will see how to integrate MetaTrader 5 and a discord server in order to receive trading notifications in real time from any location. We will see how to configure the platform and Discord to enable the delivery of alerts to Discord. We will also cover security issues which arise in connection with the use of WebRequests and webhooks for such alerting solutions.
Across Neighbourhood Search (ANS)
Across Neighbourhood Search (ANS)
The article reveals the potential of the ANS algorithm as an important step in the development of flexible and intelligent optimization methods that can take into account the specifics of the problem and the dynamics of the environment in the search space.
Building a Candlestick Trend Constraint Model (Part 9): Multiple Strategies Expert Advisor (III)
Building a Candlestick Trend Constraint Model (Part 9): Multiple Strategies Expert Advisor (III)
Welcome to the third installment of our trend series! Today, we’ll delve into the use of divergence as a strategy for identifying optimal entry points within the prevailing daily trend. We’ll also introduce a custom profit-locking mechanism, similar to a trailing stop-loss, but with unique enhancements. In addition, we’ll upgrade the Trend Constraint Expert to a more advanced version, incorporating a new trade execution condition to complement the existing ones. As we move forward, we’ll continue to explore the practical application of MQL5 in algorithmic development, providing you with more in-depth insights and actionable techniques.
Portfolio Risk Model using Kelly Criterion and Monte Carlo Simulation
Portfolio Risk Model using Kelly Criterion and Monte Carlo Simulation
For decades, traders have been using the Kelly Criterion formula to determine the optimal proportion of capital to allocate to an investment or bet to maximize long-term growth while minimizing the risk of ruin. However, blindly following Kelly Criterion using the result of a single backtest is often dangerous for individual traders, as in live trading, trading edge diminishes over time, and past performance is no predictor of future result. In this article, I will present a realistic approach to applying the Kelly Criterion for one or more EA's risk allocation in MetaTrader 5, incorporating Monte Carlo simulation results from Python.
Creating a Trading Administrator Panel in MQL5 (Part VIII): Analytics Panel
Creating a Trading Administrator Panel in MQL5 (Part VIII): Analytics Panel
Today, we delve into incorporating useful trading metrics within a specialized window integrated into the Admin Panel EA. This discussion focuses on the implementation of MQL5 to develop an Analytics Panel and highlights the value of the data it provides to trading administrators. The impact is largely educational, as valuable lessons are drawn from the development process, benefiting both upcoming and experienced developers. This feature demonstrates the limitless opportunities this development series offers in equipping trade managers with advanced software tools. Additionally, we'll explore the implementation of the PieChart and ChartCanvas classes as part of the continued expansion of the Trading Administrator panel’s capabilities.
Utilizing CatBoost Machine Learning model as a Filter for Trend-Following Strategies
Utilizing CatBoost Machine Learning model as a Filter for Trend-Following Strategies
CatBoost is a powerful tree-based machine learning model that specializes in decision-making based on stationary features. Other tree-based models like XGBoost and Random Forest share similar traits in terms of their robustness, ability to handle complex patterns, and interpretability. These models have a wide range of uses, from feature analysis to risk management. In this article, we're going to walk through the procedure of utilizing a trained CatBoost model as a filter for a classic moving average cross trend-following strategy.
Creating a Trading Administrator Panel in MQL5 (Part VII): Trusted User, Recovery and Cryptography
Creating a Trading Administrator Panel in MQL5 (Part VII): Trusted User, Recovery and Cryptography
Security prompts, such as those triggered every time you refresh the chart, add a new pair to the chat with the Admin Panel EA, or restart the terminal, can become tedious. In this discussion, we will explore and implement a feature that tracks the number of login attempts to identify a trusted user. After a set number of failed attempts, the application will transition to an advanced login procedure, which also facilitates passcode recovery for users who may have forgotten it. Additionally, we will cover how cryptography can be effectively integrated into the Admin Panel to enhance security.
Creating a Trading Administrator Panel in MQL5 (Part VI):Trade Management Panel (II)
Creating a Trading Administrator Panel in MQL5 (Part VI):Trade Management Panel (II)
In this article, we enhance the Trade Management Panel of our multi-functional Admin Panel. We introduce a powerful helper function that simplifies the code, improving readability, maintainability, and efficiency. We will also demonstrate how to seamlessly integrate additional buttons and enhance the interface to handle a wider range of trading tasks. Whether managing positions, adjusting orders, or simplifying user interactions, this guide will help you develop a robust, user-friendly Trade Management Panel.
Connexus Observer (Part 8): Adding a Request Observer
Connexus Observer (Part 8): Adding a Request Observer
In this final installment of our Connexus library series, we explored the implementation of the Observer pattern, as well as essential refactorings to file paths and method names. This series covered the entire development of Connexus, designed to simplify HTTP communication in complex applications.
Client in Connexus (Part 7): Adding the Client Layer
Client in Connexus (Part 7): Adding the Client Layer
In this article we continue the development of the connexus library. In this chapter we build the CHttpClient class responsible for sending a request and receiving an order. We also cover the concept of mocks, leaving the library decoupled from the WebRequest function, which allows greater flexibility for users.
Creating a Trading Administrator Panel in MQL5 (Part VI): Multiple Functions Interface (I)
Creating a Trading Administrator Panel in MQL5 (Part VI): Multiple Functions Interface (I)
The Trading Administrator's role goes beyond just Telegram communications; they can also engage in various control activities, including order management, position tracking, and interface customization. In this article, we’ll share practical insights on expanding our program to support multiple functionalities in MQL5. This update aims to overcome the current Admin Panel's limitation of focusing primarily on communication, enabling it to handle a broader range of tasks.
From Python to MQL5: A Journey into Quantum-Inspired Trading Systems
From Python to MQL5: A Journey into Quantum-Inspired Trading Systems
The article explores the development of a quantum-inspired trading system, transitioning from a Python prototype to an MQL5 implementation for real-world trading. The system uses quantum computing principles like superposition and entanglement to analyze market states, though it runs on classical computers using quantum simulators. Key features include a three-qubit system for analyzing eight market states simultaneously, 24-hour lookback periods, and seven technical indicators for market analysis. While the accuracy rates might seem modest, they provide a significant edge when combined with proper risk management strategies.
News Trading Made Easy (Part 5): Performing Trades (II)
News Trading Made Easy (Part 5): Performing Trades (II)
This article will expand on the trade management class to include buy-stop and sell-stop orders to trade news events and implement an expiration constraint on these orders to prevent any overnight trading. A slippage function will be embedded into the expert to try and prevent or minimize possible slippage that may occur when using stop orders in trading, especially during news events.
Building A Candlestick Trend Constraint Model (Part 9): Multiple Strategies Expert Advisor (II)
Building A Candlestick Trend Constraint Model (Part 9): Multiple Strategies Expert Advisor (II)
The number of strategies that can be integrated into an Expert Advisor is virtually limitless. However, each additional strategy increases the complexity of the algorithm. By incorporating multiple strategies, an Expert Advisor can better adapt to varying market conditions, potentially enhancing its profitability. Today, we will explore how to implement MQL5 for one of the prominent strategies developed by Richard Donchian, as we continue to enhance the functionality of our Trend Constraint Expert.
Exploring Cryptography in MQL5: A Step-by-Step Approach
Exploring Cryptography in MQL5: A Step-by-Step Approach
This article explores the integration of cryptography within MQL5, enhancing the security and functionality of trading algorithms. We’ll cover key cryptographic methods and their practical implementation in automated trading.
Connexus Helper (Part 5): HTTP Methods and Status Codes
Connexus Helper (Part 5): HTTP Methods and Status Codes
In this article, we will understand HTTP methods and status codes, two very important pieces of communication between client and server on the web. Understanding what each method does gives you the control to make requests more precisely, informing the server what action you want to perform and making it more efficient.
Creating a Trading Administrator Panel in MQL5 (Part IV): Login Security Layer
Creating a Trading Administrator Panel in MQL5 (Part IV): Login Security Layer
Imagine a malicious actor infiltrating the Trading Administrator room, gaining access to the computers and the Admin Panel used to communicate valuable insights to millions of traders worldwide. Such an intrusion could lead to disastrous consequences, such as the unauthorized sending of misleading messages or random clicks on buttons that trigger unintended actions. In this discussion, we will explore the security measures in MQL5 and the new security features we have implemented in our Admin Panel to safeguard against these threats. By enhancing our security protocols, we aim to protect our communication channels and maintain the trust of our global trading community. Find more insights in this article discussion.
Body in Connexus (Part 4): Adding HTTP body support
Body in Connexus (Part 4): Adding HTTP body support
In this article, we explored the concept of body in HTTP requests, which is essential for sending data such as JSON and plain text. We discussed and explained how to use it correctly with the appropriate headers. We also introduced the ChttpBody class, part of the Connexus library, which will simplify working with the body of requests.
Developing a multi-currency Expert Advisor (Part 12): Developing prop trading level risk manager
Developing a multi-currency Expert Advisor (Part 12): Developing prop trading level risk manager
In the EA being developed, we already have a certain mechanism for controlling drawdown. But it is probabilistic in nature, as it is based on the results of testing on historical price data. Therefore, the drawdown can sometimes exceed the maximum expected values (although with a small probability). Let's try to add a mechanism that ensures guaranteed compliance with the specified drawdown level.